CrewAI

CrewAI is an enterprise AI agent builder: design agent crews in Crew Studio or Python, then deploy, trace and govern them on CrewAI's cloud or in-house.

CrewAI turns a business process into a team of AI agents, each owning one role, and runs that team in production under the controls a platform group expects. The commercial platform, called CrewAI AMP in its documentation, comes from CrewAI, Inc., the Delaware company that also maintains the open-source CrewAI framework. It is built for the step after a working prototype: getting agents deployed, watched and governed across a business. Business staff and engineers work on the same platform, so a workflow is not rebuilt when it changes hands. Crew Studio is the visual editor. A person describes the job to an AI copilot, and the canvas lays the workflow out as nodes and edges that stay editable by hand. Each agent gets a role, its own model, tools from a private tool repository and knowledge sources to retrieve from. Agents can also delegate work to each other. Automations start a crew on a schedule, from a webhook or from an event in Gmail, Slack, HubSpot, Salesforce or Zapier. A deployed crew answers kickoff, status and resume calls over an API. Traces records every task, tool call and model call, and checkpoints let a failed run resume or fork. The platform suits companies moving agent pilots into governed production, where engineers write crews in Python and operations staff assemble them in the editor. Platform teams get single sign-on through Microsoft Entra or Okta, role-based access, PII redaction and policies on the Enterprise plan. That plan can also run crews in a dedicated VPC or on the customer's own infrastructure. CrewAI sells it as a free Basic workspace with a monthly cap on workflow executions, and as an Enterprise plan sized to its workflows, with a trial on request. Crews usually sit inside processes that already span several systems, reading files from Google Drive or OneDrive and updating records in HubSpot or Salesforce. Engineers who start in the open-source framework deploy the same code from GitHub, so a crew tested on a laptop runs under the platform's tracing and access rules. A human input step parks a workflow until a person answers, which keeps an approval in the loop before an agent acts. Monitoring data can flow on to Datadog, and models can come from providers such as Azure OpenAI. CrewAI fits the company whose agent ideas outnumber its platform engineers and that wants one place to build, approve and watch them.